expectations to new social learning toolsNovember 13, 2007
Social software is generally recognized as tools, which development is highly dependent of users‘ mutual interaction with the mediation of these tools, involving group processes such as discussion, mutual advice or favors, and play (Shirky, 2002).
Any activity is always mediated by the tools that we create in the process of actualizing certain affordances in our goal-directed and enculturated actions – when making something from the environment into our own or when bringing something of our own ideas into the environment. More than at earlier times, current social tools are the creation of communities. While the artifacts and meanings, created and distributed with social software, obtain in the process of use the community-defined folksonomical dimensions, the activities what are performed and evolve in these systems as a result of community interactions, have yet remained implicit, and are not well observable for the users of social software. Social software still lacks the means how to make activity potentialities of tools, and activity patterns, which emerge in the communities, more observable. What we basically lack, is the soft ontologically defined constraints/possibilities of actions determined by the communities who use social tools.
When using social software for learning at institutional courses, but also for personal self-directed learning attempts with other learners in the Web, the explicit socially defined action potentialities within activity systems would enhance the selection of communal tools for common objectives. Some of the recent developments, such as Friend of a Friend (FOAF) technology that aims at creating a Web of machine-readable pages describing people, the links between them and the things they create and do, seem to promise that the action-based automated search of learning partners would soon become possible. The best practice of the tool-use for certain learning activities is, thus, disseminated giving a valuable input for the others and narrowing down their choice of appropriate tools for particular learning goals. For example, it is suggested that the super-peer networks would enable the learners to observe, record and share their activity practices with artifacts through networks (Clematis et al., 2007). If FOAF and similar specifications could read personal action potentialities with certain social software, their communities and artifact types, which we described earlier, the decision processes at constructing collaborative landscapes for learning purposes, could be supported by technological means.
Tools that support the construction of group landscapes from distributed personal tools play an important role in the application of new Learning Environment Design model. The new generation of aggregation and mashup tools is anticipated to support the construction of distributed personal and group learning landscapes, using the affordance-based activity system model. The mashup of the learning environment from distributed feeds will be realised, considering, in one hand, the anticipated affordances for action, and personal activity preferences, which may be described with FOAF kind of scripts, and on the other hand, the socially defined action potentialities of tools would enable the mashup tools to automatically select a suitable set of widgets for certain learners or groups. In these mashup tools learners would pertain full control over the selection of feeds – eventually they can ignore or close some tools and even add new tools. Such user-activity can be, in turn, used to update the semantic models refining the activity-tool relations, improving the tool recommendations.
The critical factor of effective use of distributed social landscapes and scaffolding in such systems is the possibility to monitor the use of landscape elements and the information flows between them in the cause of action. New developments at social software systems enable already to visualise the folksonomy based meaning-building dimensions in the communities (see Klerkx & Duval, 2007). What is yet needed, is the visualisation of activities and learning landscapes for the learners. This may be realised through visualising the mashed learning landscapes as affordance-based activity systems in which the distributed social tools would convey also the socially defined activity potentials. Certainly, this may not indicate, which of these available activity potentialities were put into action. For understanding this, interaction within specific social tools, and the content of feeds between tools must be analyzed (eg. which regulatory, social or content-creation types of action potentialities were put into action). But that seems even more complicated issue.
The joint learning situations would also pertain the use of asynchronous or synchronous interaction tools when working with artifacts. Some of the tools like Gabbly chat can now be easily integrated with different webpages, social software applications and masup tools. Yet, the develoment of tools, which keep the interrelations between the talked content and the productive actions made at artifact, should enhance learning at distributed landscapes. The future of using distributed social software elements for self-directed and collaborative learning purposes is in mashing selectively the evidence from different activities eg. weblog posts and commentaries with certain tags, artifacts purposfully created and stored in different repositories, wiki-contributions, discourse logs etc. In these places (hubs) where our distributed knowledge meets again, we propagate ourselves as the connectors between the communities. If we mix our distributed self with the knowledge of our community members (like in micro-blogging feeds of Jaiku), these mashed feeds may work as triggers for learning. They enable to access knowledge community-wise and transfer it to other community spaces.